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High-Tech Industrial Agglomeration, Government Intervention and Regional Energy Efficiency: Based on the Perspective of the Spatial Spillover Effect and Panel Threshold Effect

Author

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  • Yuxi Chen

    (Business School, Ningbo University, Ningbo 315211, China)

  • Mengting Zhang

    (Business School, Ningbo University, Ningbo 315211, China
    Central and Eastern European Countries Economic and Trade Cooperation Institute, Ningbo University, Ningbo 315211, China)

  • Chencheng Wang

    (Business School, Ningbo University, Ningbo 315211, China)

  • Xin Lin

    (School of Finance and Management, Zhejiang Financial College, Hangzhou 310018, China)

  • Zhijie Zhang

    (College of Resources & Environmental Science, Shijiazhuang University, Shijiazhuang 050035, China)

Abstract

Improving energy efficiency is an important breakthrough to effectively solve the contradiction between economic development and environmental protection. Using a fixed-effect model, spatial Durbin model and panel threshold model, this paper takes panel data of 30 provinces, municipalities and autonomous regions (except Tibet) in mainland China from 2007 to 2019 as samples to demonstrate the impact of high-tech industry agglomeration and government intervention on regional energy efficiency and the mechanism among the three. The results show that high-tech industry agglomeration has a significant positive impact on regional energy efficiency, and government intervention has a significant inhibitory effect on regional energy efficiency. When the three factors act together, government intervention has a distorting effect on the impact of high-tech industry agglomeration on energy efficiency. Both high-tech industrial agglomeration and energy efficiency have spatial spillover effects. The impact of high-tech industry agglomeration on energy efficiency has significant spatial heterogeneity. Based on the above analysis and conclusion, practical policy suggestions are put forward to achieve the goal of improving energy efficiency and effectively solving the contradiction between economic development and environmental protection.

Suggested Citation

  • Yuxi Chen & Mengting Zhang & Chencheng Wang & Xin Lin & Zhijie Zhang, 2023. "High-Tech Industrial Agglomeration, Government Intervention and Regional Energy Efficiency: Based on the Perspective of the Spatial Spillover Effect and Panel Threshold Effect," Sustainability, MDPI, vol. 15(7), pages 1-29, April.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:7:p:6295-:d:1117370
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    References listed on IDEAS

    as
    1. Jean Tirole, 1988. "The Theory of Industrial Organization," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262200716, April.
    2. Tan, Xiujie & Liu, Yishuang & Dong, Hanmin & Zhang, Zhan, 2022. "The effect of carbon emission trading scheme on energy efficiency: Evidence from China," Economic Analysis and Policy, Elsevier, vol. 75(C), pages 506-517.
    3. Philippe Aghion & Nick Bloom & Richard Blundell & Rachel Griffith & Peter Howitt, 2005. "Competition and Innovation: an Inverted-U Relationship," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 120(2), pages 701-728.
    4. Tanaka, Kenta & Managi, Shunsuke, 2021. "Industrial agglomeration effect for energy efficiency in Japanese production plants," Energy Policy, Elsevier, vol. 156(C).
    5. Witajewski-Baltvilks, Jan & Verdolini, Elena & Tavoni, Massimo, 2015. "Directed Technological Change and Energy Efficiency Improvements," Climate Change and Sustainable Development 208910, Fondazione Eni Enrico Mattei (FEEM).
    6. Hansen, Bruce E., 1999. "Threshold effects in non-dynamic panels: Estimation, testing, and inference," Journal of Econometrics, Elsevier, vol. 93(2), pages 345-368, December.
    7. Sanghoon Ahn, 1999. "Technology Upgrading with Learning Cost: A Solution for Two ‘Productivity Puzzles'," OECD Economics Department Working Papers 220, OECD Publishing.
    8. Xu, Mengmeng & Tan, Ruipeng & He, Xinju, 2022. "How does economic agglomeration affect energy efficiency in China?: Evidence from endogenous stochastic frontier approach," Energy Economics, Elsevier, vol. 108(C).
    9. Gao, Da & Li, Ge & Yu, Jiyu, 2022. "Does digitization improve green total factor energy efficiency? Evidence from Chinese 213 cities," Energy, Elsevier, vol. 247(C).
    10. Carlino, Gerald A. & Chatterjee, Satyajit & Hunt, Robert M., 2007. "Urban density and the rate of invention," Journal of Urban Economics, Elsevier, vol. 61(3), pages 389-419, May.
    11. Tan, Xiujie & Xiao, Ziwei & Liu, Yishuang & Taghizadeh-Hesary, Farhad & Wang, Banban & Dong, Hanmin, 2022. "The effect of green credit policy on energy efficiency: Evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    12. Fisher-Vanden, Karen & Jefferson, Gary H. & Jingkui, Ma & Jianyi, Xu, 2006. "Technology development and energy productivity in China," Energy Economics, Elsevier, vol. 28(5-6), pages 690-705, November.
    13. Goolsbee, Austan, 1998. "Does Government R&D Policy Mainly Benefit Scientists and Engineers?," American Economic Review, American Economic Association, vol. 88(2), pages 298-302, May.
    14. Kassouri, Yacouba, 2022. "Fiscal decentralization and public budgets for energy RD&D: A race to the bottom?," Energy Policy, Elsevier, vol. 161(C).
    15. Hong, Qianqian & Cui, Linhao & Hong, Penghui, 2022. "The impact of carbon emissions trading on energy efficiency: Evidence from quasi-experiment in China's carbon emissions trading pilot," Energy Economics, Elsevier, vol. 110(C).
    16. Shanzi Ke & Edward Feser, 2010. "Count on the Growth Pole Strategy for Regional Economic Growth? Spread-Backwash Effects in Greater Central China," Regional Studies, Taylor & Francis Journals, vol. 44(9), pages 1131-1147.
    17. Qu, Chenyao & Shao, Jun & Shi, Zhenkai, 2020. "Does financial agglomeration promote the increase of energy efficiency in China?," Energy Policy, Elsevier, vol. 146(C).
    18. Ding, Jian & Liu, Baoliu & Shao, Xuefeng, 2022. "Spatial effects of industrial synergistic agglomeration and regional green development efficiency: Evidence from China," Energy Economics, Elsevier, vol. 112(C).
    19. Anel Kireyeva & Dinara Mussabalina & Baurzhan Tolysbaev, 2018. "Assessment and Identification of the Possibility for Creating IT Clusters in Kazakhstan Regions," Economy of region, Centre for Economic Security, Institute of Economics of Ural Branch of Russian Academy of Sciences, vol. 1(2), pages 463-473.
    20. Li, Bo & Han, Yukai & Wang, Chensheng & Sun, Wei, 2022. "Did civilized city policy improve energy efficiency of resource-based cities? Prefecture-level evidence from China," Energy Policy, Elsevier, vol. 167(C).
    21. J. Elhorst, 2010. "Applied Spatial Econometrics: Raising the Bar," Spatial Economic Analysis, Taylor & Francis Journals, vol. 5(1), pages 9-28.
    22. He, Pinglin & Sun, Yulong & Niu, Hanlu & Long, Chengfeng & Li, Shufeng, 2021. "The long and short-term effects of environmental tax on energy efficiency: Perspective of OECD energy tax and vehicle traffic tax," Economic Modelling, Elsevier, vol. 97(C), pages 307-325.
    23. Li, Shan & Liu, Jianjiang & Shi, Daqian, 2021. "The impact of emissions trading system on corporate energy efficiency: Evidence from a quasi-natural experiment in China," Energy, Elsevier, vol. 233(C).
    24. J. Paul Elhorst, 2014. "Matlab Software for Spatial Panels," International Regional Science Review, , vol. 37(3), pages 389-405, July.
    25. Yuan, Huaxi & Feng, Yidai & Lee, Chien-Chiang & Cen, Yan, 2020. "How does manufacturing agglomeration affect green economic efficiency?," Energy Economics, Elsevier, vol. 92(C).
    26. Liu, Zheming & Zeng, Saixing & Jin, Zhizhou & Shi, Jonathan Jingsheng, 2022. "Transport infrastructure and industrial agglomeration: Evidence from manufacturing industries in China," Transport Policy, Elsevier, vol. 121(C), pages 100-112.
    27. Wu, Jianxin & Xu, Hui & Tang, Kai, 2021. "Industrial agglomeration, CO2 emissions and regional development programs: A decomposition analysis based on 286 Chinese cities," Energy, Elsevier, vol. 225(C).
    28. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    29. Xie, Rui & Fu, Wei & Yao, Siling & Zhang, Qi, 2021. "Effects of financial agglomeration on green total factor productivity in Chinese cities: Insights from an empirical spatial Durbin model," Energy Economics, Elsevier, vol. 101(C).
    30. Dong, Feng & Li, Yangfan & Li, Kun & Zhu, Jiao & Zheng, Lu, 2022. "Can smart city construction improve urban ecological total factor energy efficiency in China? Fresh evidence from generalized synthetic control method," Energy, Elsevier, vol. 241(C).
    31. Han, Feng & Xie, Rui & Fang, Jiayu, 2018. "Urban agglomeration economies and industrial energy efficiency," Energy, Elsevier, vol. 162(C), pages 45-59.
    32. Kondo, Hiroki, 2013. "International R&D subsidy competition, industrial agglomeration and growth," Journal of International Economics, Elsevier, vol. 89(1), pages 233-251.
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    2. Hongying Zhang & Chengxuan Geng & Dongqin Cao & Jiahui Wei, 2024. "Can high-tech industrial convergence promote green innovation efficiency? Evidence from 30 Chinese provinces," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(9), pages 23579-23611, September.

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